Custom AI Models

We work across the full landscape: cloud APIs from OpenAI (GPT-5.5, Codex, o-series), Anthropic (Claude Fable 5, Opus, Sonnet, Haiku), Google (Gemini 3.1), xAI, Mistral and DeepSeek — plus open-weight models including Qwen, GLM, DeepSeek, Kimi, MiniMax, Llama, Gemma, Phi and Nemotron.

It depends on your data sensitivity, request volume and budget. APIs win on speed to market and access to frontier capability; self-hosted open-weight models win on data control, predictable costs at scale and independence from vendor terms. Many of our clients end up with a hybrid of both.

Yes — today's leading open-weight models deliver frontier-level coding and reasoning with up to 1M-token context. For many workloads the quality gap versus proprietary APIs has effectively closed, while the cost and privacy advantages remain.

In most cases yes. Models under Apache 2.0 or MIT (Qwen, GLM, DeepSeek, Mistral, Gemma, Phi) are clean for commercial use. Custom licenses like Meta's Llama terms include usage caps and regional restrictions — we review those against your specific case before deployment.

It varies from a single GPU for compact models like Mistral Small 4 or Phi-4 to multi-GPU clusters for large mixture-of-experts models. We size the infrastructure to your workload and can deploy on your hardware, your cloud accounts or our managed environment.

Yes. We handle provider migrations end to end: prompt and output compatibility testing, quality benchmarking before and after, cost comparison, and a routing layer that lets you switch or mix providers without rewriting your product.

We run your representative tasks through candidate models and measure quality, latency and cost per task — then factor in licensing, data residency and your team's stack. The recommendation comes with numbers, not opinions.

API integration projects depend on scope and the number of systems involved. Self-hosted deployments add infrastructure sizing and serving setup. After a short discovery we provide an estimate covering both the build and the ongoing run costs.